Discovering most classificatory patterns for very expressive pattern classes

Masayuki Takeda, Shunsuke Inenaga, Hideo Bannai, Ayumi Shinohara, Setsuo Arikawa

研究成果: Article

14 被引用数 (Scopus)

抄録

The classificatory power of a pattern is measured by how well it separates two given sets of strings. This paper gives practical algorithms to find the fixed/variable-length-don't-care pattern (FVLDC pattern) and approximate FVLDC pattern which are most classificatory for two given string sets. We also present algorithms to discover the best window-accumulated FVLDC pattern and window-accumulated approximate FVLDC pattern. All of our new algorithms run in practical amount of time by means of suitable pruning heuristics and fast pattern matching techniques.

本文言語English
ページ(範囲)486-493
ページ数8
ジャーナルLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
2843
DOI
出版ステータスPublished - 2003

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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